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Architecture

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Part of the book series: SpringerBriefs in Computer Science ((BRIEFSCOMPUTER))

Abstract

Sensors are basic components for all sensor networks, and their quality depends heavily on industry advances in signal conditioning and processing, microelectromechanical systems (MEMS), and nanotechnology.

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References

  • Acock, A. C. (2005). Working with missing values. J Marriage Fam, 1012–1028.

    Google Scholar 

  • Bao, S. D., Zhang, Y. T., & Shen, L. F. (2005). Physiological signal based entity authentication for body area sensor networks and mobile healthcare systems. Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. IEEE.

    Google Scholar 

  • Bickel, P. J., & Freedman, D. A. (1981). Some asymptotic theory for the bootstrap. Annals of Statistics, 1196–1217.

    Google Scholar 

  • Biel, L., Pettersson, O., Philipson, L., & Wide, P. (2001). Ecg analysis: a new approach in human identification. IEEE Transactions on Instrumentation and Measurement, 808–812.

    Google Scholar 

  • Bollier, D., & Firestone, C. M. (2010). The Promise and peril of big data. Washington, DC, USA: Aspen Institute, Communications and Society Program.

    Google Scholar 

  • Buck, S. F. (1960). A method of estimation of missing values in multivariate data suitable for use with an electronic computer. Journal of the Royal Statistical Society. Series B, Statistical Methodology, 302–306.

    Google Scholar 

  • Chen, M., Gonzalez, S., Vasilakos, A., Cao, H., & Leung, V. C. (2011). Body area networks: A survey. Mobile Networks and Applications, 171–193.

    Google Scholar 

  • Eysenbach, G. (2011). Consort-ehealth: Improving and standardizing evaluation reports of web-based and mobile health interventions. Journal of Medical Internet Research.

    Google Scholar 

  • Fang, H., Espy, K. A., Rizzo, M. L., Stopp, C., Wiebe, S. A., & Stroup, W. W. (2009). Pattern recognition of longitudinal trial data with nonignorable missingness: An empirical case study. International Journal of Information Technology & Decision Making, 491–513.

    Google Scholar 

  • Fang, H., Zhang, Z., Wang, C. J., Daneshmand, M., Wang, C., & Wang, H. (2015). A survey of big data research. IEEE Networks, 6–9.

    Google Scholar 

  • Fang H et al. (n.d.). Retrieved from http://www.amstat.org/meetings/jsm/2014/onlineprogram/.

  • Little, R., & Rubin, D. (2014). Statistical analysis with missing data. Wiley.

    Google Scholar 

  • Schafer, J. (1997). Analysis of incomplete multivariate data. CRC press.

    Google Scholar 

  • Shao, J. (1993). Linear model selection by cross-validation. Journal of the American Statistical Association, 486–494.

    Google Scholar 

  • Venkatasubramanian, K. K., Banerjee, A., & Gupta, S. K. (2008). Ekg-based key agreement in body sensor networks. INFOCOM Workshops, (pp. 1 –6).

    Google Scholar 

  • Venkatasubramanian, K. K., Banerjee, A., & Gupta, S. K. S. (2010). PSKA: usable and secure key agreement scheme for body area networks. Transactions on Information Technology, 60–68.

    Google Scholar 

  • Xie, X. L., & Beni, G. (1991). A validity measure for fuzzy clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 841–847.

    Google Scholar 

  • Zhang, Z., & Fang, H. (2016). Multiple-vs non-or single-imputation based fuzzy clustering for incomplete longitudinal behavioral intervention data. In 2016 IEEE first international conference on connected health: applications, systems and engineering technologies (CHASE) (pp. 219–228). IEEE.

    Google Scholar 

  • Zhang, Z., Wang, H., Vasilakos, A. V., & Fang, H. (2012). ECG-Cryptography and Authentication in Body Area Networks. IEEE Transactions on Information Technology in Biomedicine, 1070–1078.

    Google Scholar 

  • Zhang, Z., Fang, H., & Wang, H. (2015). Visualization aided engagement pattern validation for big longitudinal web behavior intervention data. In The 17th international Conference on E-health Networking, Application & Services. (IEEE Healthcom’15);. Boston, USA: IEEE.

    Google Scholar 

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Correspondence to Honggang Wang .

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Wang, H., Mahmud, M.S., Fang, H., Wang, C. (2016). Architecture. In: Wireless Health. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-47946-0_3

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  • DOI: https://doi.org/10.1007/978-3-319-47946-0_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47945-3

  • Online ISBN: 978-3-319-47946-0

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